generate_image_structured

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'fine-grained control' but lacks details on permissions, rate limits, costs, or output behavior (e.g., image URLs, processing time). For a complex tool with 17 parameters and no annotations, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise and well-structured in two sentences: the first states the purpose and key features, and the second specifies the ideal use case. Every word earns its place with no redundancy or fluff, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (17 parameters, nested objects, no output schema, and no annotations), the description is insufficient. It doesn't explain what the tool returns (e.g., image data or URLs), potential errors, or behavioral traits like costs or limitations. For such a rich input schema, more contextual information is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 88%, which is high, so the baseline score is 3. The description adds minimal value beyond the schema by listing key control aspects ('composition, style, lighting, and subjects'), but doesn't provide additional syntax, examples, or constraints for the parameters. It compensates slightly for the 12% coverage gap but not substantially.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Generate images with detailed structured prompts for precise control over composition, style, lighting, and subjects.' It specifies the verb ('generate'), resource ('images'), and scope ('structured prompts'), but doesn't explicitly differentiate from sibling tools like 'generate_image' or 'compose_images', which likely offer different approaches to image generation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides implied usage guidance: 'Ideal for AI agents that need fine-grained control.' This suggests this tool is for detailed, structured prompts rather than simpler ones, but it doesn't explicitly state when to use this versus alternatives like 'generate_image' or 'compose_images', nor does it mention prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.